Senior Data Engineer – AWS

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Organize, gather, and process extensive data sets utilizing ETL tools.

• Convert client business goals into an effective information management and business intelligence strategy.

• Manage data pipelines and guarantee secure access to information.

• Develop and present metrics and dashboards from acquired data, ensuring quality and integrity.

• Engage in data platform modernization efforts, concentrating on Lakehouse architecture, governance, quality, and preparing data for analytical and AI applications.

• Design dimensional models for use by business teams, dashboards, and reports.

• Involve yourself in the entire data lifecycle: ingestion, processing, storage, transformation, consumption, and governance.

• Conduct unit tests and performance evaluations.

• Implement best practices for security, access control, and cloud monitoring.

⛳️ Requirements

• Senior-level professional with expertise in Data/AWS/AI.

• Proficient in data extraction, transformation, and loading (ETL) tools.

• Skilled in Python / PySpark.

• Strong understanding of AWS Glue, EMR, Athena, SNS, Lambda, Step Functions, S3, Lake Formation, IAM, and CloudWatch.

• Experience with modeling and NoSQL databases such as MongoDB, DynamoDB, and Hadoop.

• Familiarity with Lakehouse architecture using Apache Iceberg, including management of analytical tables, versioning, schema evolution, partitioning, and performance enhancement.

• Experience with query engines capable of handling large volumes: Athena, Trino, Presto, or Spark SQL.

• Ability to optimize queries and work with columnar formats like Parquet and ORC.

• Knowledge of dimensional modeling, including fact and dimension tables, granularity, keys, hierarchies, metrics, and KPIs.

• Experience with structured, semi-structured, and unstructured data.

• Strong proficiency in artificial intelligence is essential.

• Preferred: AWS Practitioner and AWS Data Engineer certifications.

• Preferred: experience in data quality and observability.

• Preferred: experience with infrastructure-as-code tools, such as Terraform and CloudWatch.

• Preferred: understanding of Data Mesh.

• Preferred: knowledge of applied AI for data, including feature stores and integration of pipelines with AI models.

🏝️ Benefits

• Multi-benefit card – select how and where to utilize it.

• Scholarships for Undergraduate, Postgraduate, MBA, and Language courses.

• Certification incentive programs.

• Flexible working hours.

• Competitive salaries.

• Annual performance review with a structured career development plan.

• Opportunities for international career advancement.

• Wellhub and TotalPass.

• Private pension plan.

• Childcare assistance.

• Health insurance.

• Dental insurance.

• Life insurance.